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 Run in Google Colab
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 Download notebook
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 See TF Hub model
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This colab will show you how to use the SPICE model downloaded from TensorFlow Hub.
sudo apt-get install -q -y timidity libsndfile1Reading package lists... Building dependency tree... Reading state information... libsndfile1 is already the newest version (1.0.28-7ubuntu0.2). The following packages were automatically installed and are no longer required: libatasmart4 libblockdev-fs2 libblockdev-loop2 libblockdev-part-err2 libblockdev-part2 libblockdev-swap2 libblockdev-utils2 libblockdev2 libparted-fs-resize0 libxmlb2 Use 'sudo apt autoremove' to remove them. The following additional packages will be installed: fluid-soundfont-gm libao-common libao4 Suggested packages: fluid-soundfont-gs fluidsynth libaudio2 libsndio6.1 freepats pmidi timidity-daemon The following NEW packages will be installed: fluid-soundfont-gm libao-common libao4 timidity 0 upgraded, 4 newly installed, 0 to remove and 188 not upgraded. Need to get 120 MB of archives. After this operation, 150 MB of additional disk space will be used. Get:1 http://us-east1.gce.archive.ubuntu.com/ubuntu focal/universe amd64 fluid-soundfont-gm all 3.1-5.1 [119 MB] Get:2 http://us-east1.gce.archive.ubuntu.com/ubuntu focal/main amd64 libao-common all 1.2.2+20180113-1ubuntu1 [6644 B] Get:3 http://us-east1.gce.archive.ubuntu.com/ubuntu focal/main amd64 libao4 amd64 1.2.2+20180113-1ubuntu1 [35.1 kB] Get:4 http://us-east1.gce.archive.ubuntu.com/ubuntu focal/universe amd64 timidity amd64 2.14.0-8build1 [613 kB] Fetched 120 MB in 2s (64.8 MB/s) Selecting previously unselected package fluid-soundfont-gm. (Reading database ... 144021 files and directories currently installed.) Preparing to unpack .../fluid-soundfont-gm_3.1-5.1_all.deb ... Unpacking fluid-soundfont-gm (3.1-5.1) ... Selecting previously unselected package libao-common. Preparing to unpack .../libao-common_1.2.2+20180113-1ubuntu1_all.deb ... Unpacking libao-common (1.2.2+20180113-1ubuntu1) ... Selecting previously unselected package libao4:amd64. Preparing to unpack .../libao4_1.2.2+20180113-1ubuntu1_amd64.deb ... Unpacking libao4:amd64 (1.2.2+20180113-1ubuntu1) ... Selecting previously unselected package timidity. Preparing to unpack .../timidity_2.14.0-8build1_amd64.deb ... Unpacking timidity (2.14.0-8build1) ... Setting up libao-common (1.2.2+20180113-1ubuntu1) ... Setting up libao4:amd64 (1.2.2+20180113-1ubuntu1) ... Setting up fluid-soundfont-gm (3.1-5.1) ... Setting up timidity (2.14.0-8build1) ... Processing triggers for libc-bin (2.31-0ubuntu9.12) ... Processing triggers for man-db (2.9.1-1) ... Processing triggers for desktop-file-utils (0.24-1ubuntu3) ... Processing triggers for mime-support (3.64ubuntu1) ... Processing triggers for gnome-menus (3.36.0-1ubuntu1) ...
# All the imports to deal with sound datapip install pydub librosa music21
import tensorflow as tf
import tensorflow_hub as hub
import numpy as np
import matplotlib.pyplot as plt
import librosa
from librosa import display as librosadisplay
import logging
import math
import statistics
import sys
from IPython.display import Audio, Javascript
from scipy.io import wavfile
from base64 import b64decode
import music21
from pydub import AudioSegment
logger = logging.getLogger()
logger.setLevel(logging.ERROR)
print("tensorflow: %s" % tf.__version__)
#print("librosa: %s" % librosa.__version__)
tensorflow: 2.16.1
The audio input file
Now the hardest part: Record your singing! :)
We provide four methods to obtain an audio file:
- Record audio directly in colab
- Upload from your computer
- Use a file saved on Google Drive
- Download the file from the web
Choose one of the four methods below.
[Run this] Definition of the JS code to record audio straight from the browser
RECORD = """
const sleep = time => new Promise(resolve => setTimeout(resolve, time))
const b2text = blob => new Promise(resolve => {
const reader = new FileReader()
reader.onloadend = e => resolve(e.srcElement.result)
reader.readAsDataURL(blob)
})
var record = time => new Promise(async resolve => {
stream = await navigator.mediaDevices.getUserMedia({ audio: true })
recorder = new MediaRecorder(stream)
chunks = []
recorder.ondataavailable = e => chunks.push(e.data)
recorder.start()
await sleep(time)
recorder.onstop = async ()=>{
blob = new Blob(chunks)
text = await b2text(blob)
resolve(text)
}
recorder.stop()
})
"""
def record(sec=5):
try:
from google.colab import output
except ImportError:
print('No possible to import output from google.colab')
return ''
else:
print